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Implement predict & predict_proba optimization

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reduces time in two orders of magnitude in creditcard dataset
This commit is contained in:
Ricardo Montañana Gómez
2020-05-15 23:35:33 +02:00
parent e56b955b92
commit 80b5cf8e72
6 changed files with 129 additions and 59 deletions
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main.py
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@@ -33,8 +33,9 @@ def load_creditcard(n_examples=0):
print("Fraud: {0:.3f}% {1}".format(len(y[y == 1])*100/X.shape[0], len(y[y == 1])))
print("Valid: {0:.3f}% {1}".format(len(y[y == 0])*100/X.shape[0], len(y[y == 0])))
return X, y
X, y = load_creditcard(-5000)
#X, y = load_creditcard(-5000)
#X, y = load_creditcard()
X, y = load_creditcard()
clf = Stree(C=.01, max_iter=100, random_state=random_state)
clf.fit(X, y)